The DOI matches its Crossref record; 3 of the 3 references it cites were found in a registry or an index.
Core–Shell Supramolecular Gelatin Nanoparticles for Adaptive and “On-Demand” Antibiotic Delivery
Abstract
The treatment of bacterial infection is one of the most challenging tasks in the biomedical field. Antibiotics were developed over 70 years and are regarded as the most efficient type of drug to treat bacterial infection. However, there is a concern that the overuse of antibiotics can lead to a growing number of multidrug-resistant bacteria. The development of antibiotic delivery systems to improve the biodistribution and bioavailability of antibiotics is a practical strategy for reducing the generation of antibiotic resistance and increasing the lifespan of newly developed antibiotics. Here we present an antibiotic delivery system (Van⊂SGNPs@RBC) based on core-shell supramolecular gelatin nanoparticles (SGNPs) for adaptive and "on-demand" antibiotic delivery. The core composed of cross-linked SGNPs allows for bacterial infection-microenvironment responsive release of antibiotics. The shell coated with uniform red blood cell membranes executes the function of disguise for reducing the clearance by the immune system during the antibiotic delivery, as well as absorbs the bacterial exotoxin to relieve symptoms caused by bacterial infection. This approach demonstrates an innovative and biomimetic antibiotic delivery system for the treatment of bacterial infection with a minimum dose of antibiotics.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Campoccia, D., Montanaro, L., Speziale, P., & Arciola, C. R. (2010) · Biomaterials · doi:10.1016/j.biomaterials.2010.05.005 · Cited by 392
Bacteria‐Responsive Multifunctional Nanogel for Targeted Antibiotic Delivery
Xiong, M., Li, Y., Bao, Y., Yang, X., Hu, B., & Wang, J. (2012) · Advanced Materials · doi:10.1002/adma.201202847 · Cited by 299
Sémiramoth, N., Meo, C. D., Zouhiri, F., Saïd-Hassane, F., Valetti, S., Gorges, R., Nicolas, V., Poupaert, J. H., Chollet-Martin, S., Desmaële, D., et al. (2012) · ACS Nano · doi:10.1021/nn204928v · Cited by 133
Cited by
Cell Membrane Coating Nanotechnology
Fang, R. H., Kroll, A. V., Gao, W., & Zhang, L. (2018) · Advanced Materials · doi:10.1002/adma.201706759 · Cited by 1,885
Combatting antibiotic-resistant bacteria using nanomaterials
Gupta, A., Mumtaz, S., Li, C.-H., Hussain, I., & Rotello, V. M. (2019) · Chemical Society Reviews · doi:10.1039/c7cs00748e · Cited by 1,115
Cell or Cell Membrane-Based Drug Delivery Systems
Tan, S., Wu, T., Zhang, D., & Zhang, Z. (2015) · Theranostics · doi:10.7150/thno.11852 · Cited by 466
Carbon Dot-Based Platform for Simultaneous Bacterial Distinguishment and Antibacterial Applications
Yang, J., Zhang, X., Ma, Y.-H., Gao, G., Chen, X., Jia, H.-R., Li, Y.-H., Chen, Z., & Wu, F.-G. (2016) · ACS Applied Materials & Interfaces · doi:10.1021/acsami.6b10398 · Cited by 409
Nanoparticle-based local antimicrobial drug delivery
Gao, W., Chen, Y., Zhang, Y., Zhang, Q., & Zhang, L. (2018) · Advanced Drug Delivery Reviews · doi:10.1016/j.addr.2017.09.015 · Cited by 396
Metadata
- Authors
- Li, L.-L., Xu, J.-H., Qi, G.-B., Zhao, X., Yu, F., & Wang, H.
- Venue
- ACS Nano
- Publisher
- American Chemical Society (ACS)
- Published
- 2014-04-14
- Volume
- 8
- Issue
- 5
- Pages
- 4975-4983
- ISSN
- 1936-0851 (ISSN-L)
- 1936-086X
- OpenAlex
- W2330461172
- Cited by
- 291
- References
- 3
- FWCI
- 8.63
- Type
- journal article
- Language
- en
- Open access
- closed
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Core–Shell Supramolecular Gelatin Nanoparticles for Adaptive and “On-Demand” Antibiotic Delivery. https://app.cochat.ai/papers/10.1021/nn501040h
- The paper
- Li, L.-L., Xu, J.-H., Qi, G.-B., Zhao, X., Yu, F., & Wang, H. (2014). Core–Shell Supramolecular Gelatin Nanoparticles for Adaptive and “On-Demand” Antibiotic Delivery. ACS Nano. https://doi.org/10.1021/nn501040h
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.